In 2005, 212,000 new cases of breast cancer are expected, and approximately 40,000 women will die of the disease.1 Recent national figures indicate that approximately 45% of patients with breast cancer undergo primary surgical treatment with mastectomy.2 The use of breast conserving treatment (lumpectomy and radiation therapy; BCT) is increasing as primary surgical treatment for breast cancer as long term studies have documented the efficacy of BCT.3 BCT is often followed by systemic therapy with chemotherapy, hormone therapy, or both. A prerequisite for BCT is complete removal of the cancer, documented by negative margins on pathologic evaluation of the lumpectomy specimen. The presence of positive margins is associated with increased local recurrence (LR) rates, 10-15% vs. 1-10% with negative margins.4 A competing interest is the preservation of breast tissue to minimize deformity.
The importance of local recurrence is controversial. Early studies suggested that LR does not translate into death from disease.4 However, recent data showing lower LR rates and survival benefit by adding radiation therapy to mastectomy for patients with higher stage cancers indicate the potential importance of freedom from local recurrence.5 In addition, LR contributes to significant local morbidity, usually requiring a mastectomy. Finally LR contributes to the cost of care and anxiety for the patient. Despite these issues, 20-60% of patients undergoing BCT are found to have positive margins requiring additional surgical procedures, either re-excisional lumpectomies, or mastectomy.6 These additional procedures result in increased cost, increased anxiety for the patient, and, importantly, a delay in initiation of important systemic chemotherapy or radiation therapy.
Although many patients undergoing excisional breast biopsy are found to not have cancer, the wider use of pre-operative core needle biopsy has increased the preoperative diagnosis of invasive breast cancer (IBC) or ductal carcinoma in situ (DCIS). At operation, the surgeon attempts to completely resect the cancer with negative microscopic margins, but faces several difficulties. DCIS often is associated with grossly normal appearing breast tissue and no mass. Breast cancers presenting as a mass allow the surgeon to feel and see the area to be excised. However, the microscopic extent of disease is difficult to gauge. Frozen section analysis of breast biopsy margins is difficult and unreliable, because the fat content of breast tissue results in difficulty in sectioning frozen specimens. Even after standard tissue preparation over 2 days, one estimate is that more than 1,000 slices of a 2 cm biopsy specimen would be necessary to ensure completely negative margins. Pathologists have attempted to peel the external surface of a permanently fixed specimen, as one might peel an orange, to evaluate the entirety of the specimen margin. This is difficult, and impractical in most institutions, but also does not provide real time information while the patient is in the operating room.
For all of these reasons, surgeons have adopted several techniques to increase the likelihood of negative margins. They may ink the entire specimen with a single colored ink in the operating room or in the pathology suite with the pathologist. More recently, multiple colored inks have been used to mark the six sides of a cuboid breast specimen. The former method does not allow re-resection of a specific positive margin and results in resection of a larger volume of breast tissue since the cavity side with a positive margin is not known. With both approaches, the ink may creep into crevices, resulting in falsely positive margins. With the multi-colored approach, inks may run together, resulting in confusion as to the location of a specific positive margin.
Many surgeons perform wide excisions, potentially resulting in significant breast deformity that is added to by the breast shrinkage associated with radiation therapy. An effective and widely used method to enhance the likelihood of negative margins requires the surgeon, after excision of the tumor bearing specimen, to take additional slices of breast tissue from the four sides and deep surface of the open breast cavity, and submit these additional “margins” separately as the final margins. This approach eliminates any confusion as to the location of the margin. When this technique is used, additional cancer is found in 20% of additional margins when the margins of the original specimen were negative. Regardless of the technique, final pathology evaluation may take up to one week. This delay results in patient anxiety and longer time to completion of the patient's surgical treatment. A method for reliable, intra-operative margin evaluation would be of great value for breast cancer surgery.
Sentinel lymph node biopsy (SLNB) has replaced elective lymph node dissection (ELND) of the ipsilateral axilla for patients with invasive breast cancer. Because of the high negative predictive value of SLNB patients with negative sentinel nodes are spared the need for a complete axillary dissection, with its attendant morbidity and cost. Patients with positive nodes may undergo complete axillary dissection synchronously if a frozen section pathology report is positive. The accuracy of sentinel node evaluation by frozen section is problematic,6 with a significant false negative risk, when compared to the final report. To avoid giving patients bad news after an initial favorable report, many surgeons avoid frozen section entirely, waiting up to a week for the final pathology evaluation to decide whether a patient needs additional surgery. That additional surgery may take place 1-2 weeks later. Lymph nodes containing malignant cells may have altered blood flow, which may be seen by Hyperspectral imaging. A reliable, real time method which accurately predicts lymph node metastasis would allow synchronous and complete management of the axilla, and reduce or eliminate additional anesthesias and operations.7 Lymphomas, which include Hodgkin's disease and non-Hodgkin's lymphoma, are the fifth most common type of cancer diagnosed and the sixth most common cause of cancer death in the United States. Of the two basic lymphoma types, non-Hodgkin's lymphoma is the more common, with 16,000 new cases diagnosed annually.8 The age-adjusted incidence rate of non-Hodgkin's lymphoma among non-Hispanic white men (the demographic group with the greatest preponderance) is 19.1 per 100,000 and among non-Hispanic white women are 12.0 per 100,000. Not unexpectedly, incidence rates increase with age, with a 5-fold increase from ages 30-54 to 70 and older for non-Hispanic white men, but 16-fold among Filipino women, the group with the greatest increase. However, leukemia and lymphoma also account for about half of the new cancer cases in children. Pre-clinical detection and intervention are likely to achieve a reduction in these rates. Patients already treated for lymphoma are at the greatest risk. Significantly, a study of patients monitored intensively for relapse (by physical examination, serum analysis, chest X-ray, gallium and CT scanning, ultrasound and bone marrow biopsy) determined that, in 91% of patients, relapse was detected at unscheduled visits for symptomatic disease.9 Furthermore, standard chemotherapy is effective in only 40% of patients. Clearly, new and more effective measures are needed, such as high resolution hyperspectral imaging of physiologic biomarkers for early detection of relapse.
A method for non-invasive evaluation of the progression of non-Hodgkin's lymphoma (NHL) and responses to therapy would be highly advantageous, having utility as both a non-destructive animal research tool, and as a non-invasive clinical tool, which greatly improve diagnostic efficiency. Disease progression can be evaluated in solid tissue such as the spleen and from monitoring leukemic cells in blood and lymph nodes, in addition to monitoring systemic microvascular effects induced by the disease.
Differentiating between types of tissue is useful in the medical and surgical arenas. This includes differentiating between types of normal tissue or between varieties of normal tissue types and distinguishing them from tumor tissue.
Hyperspectral Imaging System
Hyperspectral imaging (HSI) is a novel method of “imaging spectroscopy” that generates a map of a region of interest based on local chemical composition. HSI has been used in non-medical applications including satellite investigation to indicate areas of chemical weapons production and to assess the condition of agricultural fields. HSI has recently been applied to the investigation of physiologic and pathologic changes in living tissue in animal and human studies to provide information as to the health or disease of tissue that is otherwise unavailable. MHSI has been shown to accurately predict viability and survival of tissue deprived of adequate perfusion, and to differentiate diseased tissue (e.g. tumor) and growth due to cancerous angiogenesis in a rat model system of breast cancer.
HSI is a remote sensing technology in which a 2-dimensional image is created having spectral data inherent in each pixel. These stacks of images comprise what is called a hypercube. It is possible to correlate the spectrum of each pixel with the presence and concentration of various chemical species. This data can than be interpreted as a “gradient map” of these species in a surface. In essence, HSI is a method of “imaging spectroscopy” combining the chemical specificity of spectroscopy with the spatial resolution of imaging.i Light is separated into hundreds of wavelengths using a spectral separator and collected on a charge-coupled device (CCD) or a complementary metal oxide semiconductor (CMOS) sensor in much the same way that a picture is taken by an ordinary camera. Used for decades by the military, major airborne applications now are also in mineral exploration and environmental and agricultural assessmentsii,iii,iv,v 
Biological tissues also have optical signatures that reflect their chemical characteristics. The primary absorbers in tissue are oxy and deoxy-hemoglobin, hemoglobin breakdown products (e.g. bilirubin and methemoglobin), melanin (in skin), lipids and water. The in-vivo absorption spectra of these compounds are well characterized.vi By comparing collected spectra to standard in-vivo absorption spectra, information about the type, location and relative concentration of chromophores may be quantified.vii, viii The use of MHSI in-vivo provides quantification of several parameters important in the assessment of physiology. These include oxygen delivery, oxygen extraction (correlated with tissue metabolism), total hemoglobin (correlated with perfusion) and water (correlated with tissue edema) with spatial patterns at the level of the microcirculation. Optical scattering also changes in cancerous regions due to an increased number of cells with enlarged nuclei. Scattering from mitotic spindles also increases due to the act that a larger fraction of cells at any one time are undergoing mitosis. We have utilized the spectral and spatial features provided by MHSI to differentiate diseased or cancerous tissue from normal tissue and to deliver information about the “functional anatomy” of the microcirculation associated with local changes due to angiogenesis, infection, inflammation, ischemia and the impact of local tumor metabolism and surrounding tissue response.ix 
HSI has been applied to biomedicine as a non-invasive diagnostic. MHSI is non-contact, camera-based, near-real time, and able to interface with potential patients a wide variety of settings, either in a diagnostic clinic or as a monitoring tool during surgery. MHSI has been applied toward the early determination of shock, the diagnosis of foot ulcers and foot microcirculation in diabetes, and in the evaluation of resective surgery in breast cancer. MHSI can also utilize local information to evaluate systemic physiology and pathology and has demonstrated this ability in applications such as shockx,xi,xii and progression of diabetesxiii.
Significance of Hyperspectral Imaging in Cancer Diagnosis
HSI has the ability to transcend the limitations of the human eye and deliver information present in the electromagnetic spectrum that is otherwise outside the range of our vision (e.g. IR, UV, etc.) and that is beyond the level of our eye to discriminate (e.g. subtle wavelength shifts corresponding to the shifting oxygenation state of hemoglobin). With respect to cancer diagnosis, development of a Hyperspectral Cancer Detection (HCD) system provides quantitative diagnostic information at a time when clinical signs would be non-descript, inconclusive, or simply absent. The early determination of disease onset or progression or the more precise delineation of tumor margins or grade would clearly enhance the power of intervention. As a novel non-invasive, near-real time tool, HCD has the potential to widely impact on the care of the cancer patient.
The present invention uses real time intraoperative margin examination to decrease the time for completion of surgical treatment and overall breast cancer treatment. It significantly reduces cost related to operative time and reoperative time as well reducing wait time between procedures. It also reduces patient anxiety waiting to complete their surgical therapy.
MHSI also has potential for margin evaluation with many other tumor types and thus can be applied to many endoscopic procedures, including but not limited to, laparoscopy, colonoscopy, thoracoscopy, cystoscopy, hysteroscopy, bronchoscopy, and mediastinoscopy. Skin cancers, including squamous cell and basal cell carcinoma, are treated by local surgical resection with frozen section analysis of the margins. Often, the resection of several additional margins is needed to completely remove the cancer and, during this time, the surgeon and patient are idle in the operating room.
Gastrointestinal cancers, such as those of the esophagus and stomach, are known to infiltrate in submucosal planes, at some distance from the main mass. Achieving negative margins at the proximal and distal ends of resection is a standard goal of surgery of these cancers. Real time recognition of residual cancer cells at these margins would reduce operative times. However, real time recognition is not limited to residual tumors, identification of tumors versus normal tissue cysts is another embodiment of the present invention. The same is said for biliary and pancreatic cancers.
Proper management of sarcomas is contingent upon achieving negative margins. Many patients are found to have microscopically positive margins despite what appears, grossly, to be an adequately wide excision. It has been shown in numerous studies that liver resection for colorectal metastases with positive margins is associated with a much higher recurrence rate and survival than when margins of resection are negative, and in particular, exceed 1 cm.7 
With pulmonary resection for lung cancer, clearance of the cancer at the bronchial stump margin is necessary. Negative margin excision is critical in the surgical treatment of cancers of the head and neck. At the same time, tissue conservation is critical to reduce the potential resulting deformity. Real time margin assessment would be invaluable.
Spectroscopy is used to assess optical properties (e.g., reflectance, absorbance, scattering) of materials of different composition and state. In medical applications, spectroscopy is widely used for in-vivo measurements that assess the condition of a biological system, such as skin, tissue, or an organ. Once spectroscopy is performed simultaneously over a large area, it is called hyperspectral imaging. A simplified biological multi-spectral imaging apparatus is a human eye that captures reflected light at essentially three wavelength (red, green, and blue) and, once processed by a human brain, allows us to make conclusion about physiological state (e.g., if a person is hot—their skin looks red).
The development of a hyperspectral imaging apparatus for medical applications allows for expansion of the limitation of a human eye. Now it is possible to acquire reflected light at hundreds of wavelengths under a minute over large areas. As a result, a three dimensional array of data (3D data cube) is obtained, containing an enormous amounts of spatial and spectral information about the sample from which the data was acquired.
Currently, there is no brain-like algorithm that can process vast amounts of spectral data, to facilitate the assessment of physiological conditions such as tissue viability or to make diagnoses or decisions in real life situations such as during surgery or critical care in the emergency room. The volume of information contained in spectroscopic images makes standard data processing techniques time consuming and cumbersome. Furthermore, many techniques rely on matching to “learning” curves that require measurement of reference samples (controls) to create a library of spectra to facilitate the identification of chemically related compounds.
The assessment of the metabolic state of tissue is important in areas such as cancer detection, assessing surgical margins, screening for and monitoring diabetes, and for monitoring shock. In many life situations (e.g. operating, emergency room or physician visit room), the assessment of the metabolic state, or physiologic condition is necessary in real-time. That requires a computerized algorithm that pulls out the most critical features from the vast amount of hyperspectral information captured and presents results in an easily assessable color (or pseudo-color) image that can be interpreted by a person making decisions in the time-pressing environments.
For example, in U.S. Pat. No. 5,782,770 Hyperspectral imaging methods and apparatus for non-invasive diagnosis of tissue for cancer, by Mooradian, et al., an imaging device is described for capturing hyperspectral images of tissue and specifically for capturing hyperspectral information that relates to the diagnosis of cancerous tissue.
U.S. Pat. No. 6,640,130 Integrated imaging apparatus, by Freeman, et al., discusses application of a hyperspectral imager such as surgery, clinical procedures, tissue assessment, diagnostic procedures, health monitoring, and other medical valuations, especially when used in combination with other monitors of physiological assessment.
U.S. Pat. No. 6,750,964 Spectral imaging methods and systems, by Levenson and Miller, discusses general, methods of image processing (based on at least one of principal component analysis, projection pursuit, independent component analysis, convex-hull analysis, and machine learning) in application to hyperspectral cubes. In one embodiment, uses reference and target samples to build training tests and therefore cannot be performed in near real-time without preparation. Another disadvantage is that '964 also requires prior library of spectra for different tissue types, classifies each pixel based on correlation to the library samples.
U.S. Pat. No. 6,937,885, Multispectral/Hyperspectral Medical Instrument, by Lewis, et al., describes a medical hyperspectral/multispectral imager for assessing the viability of tissue including the detection or diagnosis of cancer using organ or tissue specific diagnostic protocol modules.
United States Patent Application No. 20010036304 Visualization and processing of multidimensional data using prefiltering and sorting criteria by Yang, et al., describes a method for handling complex multidimensional datasets generated by digital imaging spectroscopy that allows organization and analysis applying software and computer-based sorting algorithms. The sorting algorithms allow pixels or features from images and graphical data, to be rapidly and efficiently classified into meaningful groups according to defined criteria.
U.S. Pat. No. 6,810,279 Hyperspectral Imaging Calibration Device, by Mansfield et al. describes hyperspectral imaging calibration devices and methods for their use that generate images of three dimensional samples.
U.S. Pat. No. 6,640,132 Forensic Hyperspectral Instrument, by Freeman et al. describes portable imaging devices, such as hyperspectral imaging devices, useful for forensic and other analysis, and methods for using these devices. Devices of '132 provide images and patterned data arrays representing images in multiple discrete spectra that can then be summed or processed to allow for detection of patterns or anomalies in the data collected